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            >Deep Belief Net Toolbox</th>
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        <a href="deepbelief-module.html">Package&nbsp;deepbelief</a> ::
        Module&nbsp;basebm
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<h1 class="epydoc">Source Code for <a href="deepbelief.basebm-module.html">Module deepbelief.basebm</a></h1>
<pre class="py-src">
<a name="L1"></a><tt class="py-lineno"> 1</tt>  <tt class="py-line"><tt class="py-keyword">import</tt> <tt class="py-name">numpy</tt> <tt class="py-keyword">as</tt> <tt class="py-name">np</tt> </tt>
<a name="L2"></a><tt class="py-lineno"> 2</tt>  <tt class="py-line"><tt class="py-keyword">from</tt> <tt id="link-0" class="py-name" targets="Module deepbelief.rbm=deepbelief.rbm-module.html"><a title="deepbelief.rbm" class="py-name" href="#" onclick="return doclink('link-0', 'rbm', 'link-0');">rbm</a></tt> <tt class="py-keyword">import</tt> <tt id="link-1" class="py-name" targets="Class deepbelief.rbm.RBM=deepbelief.rbm.RBM-class.html"><a title="deepbelief.rbm.RBM" class="py-name" href="#" onclick="return doclink('link-1', 'RBM', 'link-1');">RBM</a></tt> </tt>
<a name="L3"></a><tt class="py-lineno"> 3</tt>  <tt class="py-line"><tt class="py-keyword">from</tt> <tt id="link-2" class="py-name" targets="Module deepbelief.gaussianrbm=deepbelief.gaussianrbm-module.html"><a title="deepbelief.gaussianrbm" class="py-name" href="#" onclick="return doclink('link-2', 'gaussianrbm', 'link-2');">gaussianrbm</a></tt> <tt class="py-keyword">import</tt> <tt id="link-3" class="py-name" targets="Class deepbelief.gaussianrbm.GaussianRBM=deepbelief.gaussianrbm.GaussianRBM-class.html"><a title="deepbelief.gaussianrbm.GaussianRBM" class="py-name" href="#" onclick="return doclink('link-3', 'GaussianRBM', 'link-3');">GaussianRBM</a></tt> </tt>
<a name="L4"></a><tt class="py-lineno"> 4</tt>  <tt class="py-line"><tt class="py-keyword">from</tt> <tt id="link-4" class="py-name" targets="Module deepbelief.semirbm=deepbelief.semirbm-module.html"><a title="deepbelief.semirbm" class="py-name" href="#" onclick="return doclink('link-4', 'semirbm', 'link-4');">semirbm</a></tt> <tt class="py-keyword">import</tt> <tt id="link-5" class="py-name" targets="Class deepbelief.semirbm.SemiRBM=deepbelief.semirbm.SemiRBM-class.html"><a title="deepbelief.semirbm.SemiRBM" class="py-name" href="#" onclick="return doclink('link-5', 'SemiRBM', 'link-5');">SemiRBM</a></tt> </tt>
<a name="L5"></a><tt class="py-lineno"> 5</tt>  <tt class="py-line"> </tt>
<a name="L6"></a><tt class="py-lineno"> 6</tt>  <tt class="py-line"><tt class="py-name">__license__</tt> <tt class="py-op">=</tt> <tt class="py-string">'MIT License &lt;http://www.opensource.org/licenses/mit-license.php&gt;'</tt> </tt>
<a name="L7"></a><tt class="py-lineno"> 7</tt>  <tt class="py-line"><tt class="py-name">__author__</tt> <tt class="py-op">=</tt> <tt class="py-string">'Lucas Theis &lt;lucas@tuebingen.mpg.de&gt;'</tt> </tt>
<a name="L8"></a><tt class="py-lineno"> 8</tt>  <tt class="py-line"><tt class="py-name">__docformat__</tt> <tt class="py-op">=</tt> <tt class="py-string">'epytext'</tt> </tt>
<a name="L9"></a><tt class="py-lineno"> 9</tt>  <tt class="py-line"> </tt>
<a name="BaseBM"></a><div id="BaseBM-def"><a name="L10"></a><tt class="py-lineno">10</tt> <a class="py-toggle" href="#" id="BaseBM-toggle" onclick="return toggle('BaseBM');">-</a><tt class="py-line"><tt class="py-keyword">class</tt> <a class="py-def-name" href="deepbelief.basebm.BaseBM-class.html">BaseBM</a><tt class="py-op">(</tt><tt class="py-base-class">RBM</tt><tt class="py-op">,</tt> <tt class="py-base-class">GaussianRBM</tt><tt class="py-op">,</tt> <tt class="py-base-class">SemiRBM</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="BaseBM-collapsed" style="display:none;" pad="++" indent="++++"></div><div id="BaseBM-expanded"><a name="L11"></a><tt class="py-lineno">11</tt>  <tt class="py-line">        <tt class="py-docstring">"""</tt> </tt>
<a name="L12"></a><tt class="py-lineno">12</tt>  <tt class="py-line"><tt class="py-docstring">        A helper class that takes a Boltzmann machine and fits a simpler model to it.</tt> </tt>
<a name="L13"></a><tt class="py-lineno">13</tt>  <tt class="py-line"><tt class="py-docstring">        The partition function of the simpler model is then computed.</tt> </tt>
<a name="L14"></a><tt class="py-lineno">14</tt>  <tt class="py-line"><tt class="py-docstring">        An instance of a C{BaseBM} can act as a L{RBM}, L{GaussianRBM} or L{SemiRBM}.</tt> </tt>
<a name="L15"></a><tt class="py-lineno">15</tt>  <tt class="py-line"><tt class="py-docstring">        """</tt> </tt>
<a name="L16"></a><tt class="py-lineno">16</tt>  <tt class="py-line"> </tt>
<a name="BaseBM.__init__"></a><div id="BaseBM.__init__-def"><a name="L17"></a><tt class="py-lineno">17</tt> <a class="py-toggle" href="#" id="BaseBM.__init__-toggle" onclick="return toggle('BaseBM.__init__');">-</a><tt class="py-line">        <tt class="py-keyword">def</tt> <a class="py-def-name" href="deepbelief.basebm.BaseBM-class.html#__init__">__init__</a><tt class="py-op">(</tt><tt class="py-param">self</tt><tt class="py-op">,</tt> <tt class="py-param">model</tt><tt class="py-op">,</tt> <tt class="py-param">num_samples</tt><tt class="py-op">=</tt><tt class="py-number">1000</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
</div><div id="BaseBM.__init__-collapsed" style="display:none;" pad="++" indent="++++++++++++"></div><div id="BaseBM.__init__-expanded"><a name="L18"></a><tt class="py-lineno">18</tt>  <tt class="py-line">                <tt class="py-docstring">"""</tt> </tt>
<a name="L19"></a><tt class="py-lineno">19</tt>  <tt class="py-line"><tt class="py-docstring">                Takes a Boltzmann machine and fits a simpler model to it.</tt> </tt>
<a name="L20"></a><tt class="py-lineno">20</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L21"></a><tt class="py-lineno">21</tt>  <tt class="py-line"><tt class="py-docstring">                @type  model: AbstractBM</tt> </tt>
<a name="L22"></a><tt class="py-lineno">22</tt>  <tt class="py-line"><tt class="py-docstring">                @param model: an L{RBM}, L{GaussianRBM} or L{SemiRBM}</tt> </tt>
<a name="L23"></a><tt class="py-lineno">23</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
<a name="L24"></a><tt class="py-lineno">24</tt>  <tt class="py-line"><tt class="py-docstring">                @type  num_samples: integer</tt> </tt>
<a name="L25"></a><tt class="py-lineno">25</tt>  <tt class="py-line"><tt class="py-docstring">                @param num_samples: number of samples used to estimate the mean activity</tt> </tt>
<a name="L26"></a><tt class="py-lineno">26</tt>  <tt class="py-line"><tt class="py-docstring">                of the given model's visible units</tt> </tt>
<a name="L27"></a><tt class="py-lineno">27</tt>  <tt class="py-line"><tt class="py-docstring">                """</tt> </tt>
<a name="L28"></a><tt class="py-lineno">28</tt>  <tt class="py-line"> </tt>
<a name="L29"></a><tt class="py-lineno">29</tt>  <tt class="py-line">                <tt class="py-name">samples</tt> <tt class="py-op">=</tt> <tt class="py-name">model</tt><tt class="py-op">.</tt><tt id="link-6" class="py-name" targets="Method deepbelief.abstractbm.AbstractBM.sample()=deepbelief.abstractbm.AbstractBM-class.html#sample,Method deepbelief.dbn.DBN.sample()=deepbelief.dbn.DBN-class.html#sample,Method deepbelief.mixbm.MixBM.sample()=deepbelief.mixbm.MixBM-class.html#sample"><a title="deepbelief.abstractbm.AbstractBM.sample
deepbelief.dbn.DBN.sample
deepbelief.mixbm.MixBM.sample" class="py-name" href="#" onclick="return doclink('link-6', 'sample', 'link-6');">sample</a></tt><tt class="py-op">(</tt><tt class="py-name">num_samples</tt><tt class="py-op">,</tt> <tt class="py-number">100</tt><tt class="py-op">,</tt> <tt class="py-number">20</tt><tt class="py-op">,</tt> <tt class="py-number">50</tt><tt class="py-op">)</tt> </tt>
<a name="L30"></a><tt class="py-lineno">30</tt>  <tt class="py-line">                <tt class="py-name">sample_mean</tt> <tt class="py-op">=</tt> <tt class="py-name">samples</tt><tt class="py-op">.</tt><tt class="py-name">mean</tt><tt class="py-op">(</tt><tt class="py-number">1</tt><tt class="py-op">)</tt> </tt>
<a name="L31"></a><tt class="py-lineno">31</tt>  <tt class="py-line"> </tt>
<a name="L32"></a><tt class="py-lineno">32</tt>  <tt class="py-line">                <tt class="py-keyword">if</tt> <tt class="py-name">model</tt><tt class="py-op">.</tt><tt class="py-name">__class__</tt> <tt class="py-keyword">is</tt> <tt id="link-7" class="py-name"><a title="deepbelief.semirbm.SemiRBM" class="py-name" href="#" onclick="return doclink('link-7', 'SemiRBM', 'link-5');">SemiRBM</a></tt><tt class="py-op">:</tt> </tt>
<a name="L33"></a><tt class="py-lineno">33</tt>  <tt class="py-line">                        <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">__class__</tt> <tt class="py-op">=</tt> <tt id="link-8" class="py-name"><a title="deepbelief.rbm.RBM" class="py-name" href="#" onclick="return doclink('link-8', 'RBM', 'link-1');">RBM</a></tt> </tt>
<a name="L34"></a><tt class="py-lineno">34</tt>  <tt class="py-line">                        <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">__class__</tt><tt class="py-op">.</tt><tt id="link-9" class="py-name" targets="Method deepbelief.abstractbm.AbstractBM.__init__()=deepbelief.abstractbm.AbstractBM-class.html#__init__,Method deepbelief.basebm.BaseBM.__init__()=deepbelief.basebm.BaseBM-class.html#__init__,Method deepbelief.dbn.DBN.__init__()=deepbelief.dbn.DBN-class.html#__init__,Method deepbelief.estimator.Estimator.__init__()=deepbelief.estimator.Estimator-class.html#__init__,Method deepbelief.gaussianrbm.GaussianRBM.__init__()=deepbelief.gaussianrbm.GaussianRBM-class.html#__init__,Method deepbelief.mixbm.MixBM.__init__()=deepbelief.mixbm.MixBM-class.html#__init__,Method deepbelief.rbm.RBM.__init__()=deepbelief.rbm.RBM-class.html#__init__,Method deepbelief.semirbm.SemiRBM.__init__()=deepbelief.semirbm.SemiRBM-class.html#__init__"><a title="deepbelief.abstractbm.AbstractBM.__init__
deepbelief.basebm.BaseBM.__init__
deepbelief.dbn.DBN.__init__
deepbelief.estimator.Estimator.__init__
deepbelief.gaussianrbm.GaussianRBM.__init__
deepbelief.mixbm.MixBM.__init__
deepbelief.rbm.RBM.__init__
deepbelief.semirbm.SemiRBM.__init__" class="py-name" href="#" onclick="return doclink('link-9', '__init__', 'link-9');">__init__</a></tt><tt class="py-op">(</tt><tt class="py-name">self</tt><tt class="py-op">,</tt> <tt class="py-name">model</tt><tt class="py-op">.</tt><tt class="py-name">X</tt><tt class="py-op">.</tt><tt class="py-name">shape</tt><tt class="py-op">[</tt><tt class="py-number">0</tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt class="py-number">0</tt><tt class="py-op">)</tt> </tt>
<a name="L35"></a><tt class="py-lineno">35</tt>  <tt class="py-line">                <tt class="py-keyword">else</tt><tt class="py-op">:</tt> </tt>
<a name="L36"></a><tt class="py-lineno">36</tt>  <tt class="py-line">                        <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">__class__</tt> <tt class="py-op">=</tt> <tt class="py-name">model</tt><tt class="py-op">.</tt><tt class="py-name">__class__</tt> </tt>
<a name="L37"></a><tt class="py-lineno">37</tt>  <tt class="py-line">                        <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">__class__</tt><tt class="py-op">.</tt><tt id="link-10" class="py-name"><a title="deepbelief.abstractbm.AbstractBM.__init__
deepbelief.basebm.BaseBM.__init__
deepbelief.dbn.DBN.__init__
deepbelief.estimator.Estimator.__init__
deepbelief.gaussianrbm.GaussianRBM.__init__
deepbelief.mixbm.MixBM.__init__
deepbelief.rbm.RBM.__init__
deepbelief.semirbm.SemiRBM.__init__" class="py-name" href="#" onclick="return doclink('link-10', '__init__', 'link-9');">__init__</a></tt><tt class="py-op">(</tt><tt class="py-name">self</tt><tt class="py-op">,</tt> <tt class="py-name">model</tt><tt class="py-op">.</tt><tt class="py-name">X</tt><tt class="py-op">.</tt><tt class="py-name">shape</tt><tt class="py-op">[</tt><tt class="py-number">0</tt><tt class="py-op">]</tt><tt class="py-op">,</tt> <tt class="py-number">0</tt><tt class="py-op">)</tt> </tt>
<a name="L38"></a><tt class="py-lineno">38</tt>  <tt class="py-line"> </tt>
<a name="L39"></a><tt class="py-lineno">39</tt>  <tt class="py-line">                <tt class="py-keyword">if</tt> <tt class="py-name">model</tt><tt class="py-op">.</tt><tt class="py-name">__class__</tt> <tt class="py-op">==</tt> <tt id="link-11" class="py-name"><a title="deepbelief.gaussianrbm.GaussianRBM" class="py-name" href="#" onclick="return doclink('link-11', 'GaussianRBM', 'link-3');">GaussianRBM</a></tt><tt class="py-op">:</tt> </tt>
<a name="L40"></a><tt class="py-lineno">40</tt>  <tt class="py-line">                        <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">b</tt> <tt class="py-op">=</tt> <tt class="py-name">sample_mean</tt> </tt>
<a name="L41"></a><tt class="py-lineno">41</tt>  <tt class="py-line">                        <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">sigma</tt> <tt class="py-op">=</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">sqrt</tt><tt class="py-op">(</tt><tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">square</tt><tt class="py-op">(</tt><tt class="py-name">samples</tt> <tt class="py-op">-</tt> <tt class="py-name">sample_mean</tt><tt class="py-op">)</tt><tt class="py-op">.</tt><tt class="py-name">mean</tt><tt class="py-op">(</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
<a name="L42"></a><tt class="py-lineno">42</tt>  <tt class="py-line">                        <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">logz</tt> <tt class="py-op">=</tt> <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">X</tt><tt class="py-op">.</tt><tt class="py-name">shape</tt><tt class="py-op">[</tt><tt class="py-number">0</tt><tt class="py-op">]</tt> <tt class="py-op">/</tt> <tt class="py-number">2.</tt> <tt class="py-op">*</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">log</tt><tt class="py-op">(</tt><tt class="py-number">2.</tt> <tt class="py-op">*</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">pi</tt><tt class="py-op">)</tt> <tt class="py-op">+</tt> <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">X</tt><tt class="py-op">.</tt><tt class="py-name">shape</tt><tt class="py-op">[</tt><tt class="py-number">0</tt><tt class="py-op">]</tt> <tt class="py-op">*</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">log</tt><tt class="py-op">(</tt><tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">sigma</tt><tt class="py-op">)</tt> </tt>
<a name="L43"></a><tt class="py-lineno">43</tt>  <tt class="py-line">                <tt class="py-keyword">else</tt><tt class="py-op">:</tt> </tt>
<a name="L44"></a><tt class="py-lineno">44</tt>  <tt class="py-line">                        <tt class="py-name">sample_mean</tt> <tt class="py-op">=</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">minimum</tt><tt class="py-op">(</tt><tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">maximum</tt><tt class="py-op">(</tt><tt class="py-number">0.1</tt><tt class="py-op">,</tt> <tt class="py-name">sample_mean</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> <tt class="py-number">0.9</tt><tt class="py-op">)</tt> </tt>
<a name="L45"></a><tt class="py-lineno">45</tt>  <tt class="py-line">                        <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">b</tt> <tt class="py-op">=</tt> <tt class="py-op">-</tt><tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">log</tt><tt class="py-op">(</tt><tt class="py-number">1.</tt> <tt class="py-op">/</tt> <tt class="py-name">sample_mean</tt> <tt class="py-op">-</tt> <tt class="py-number">1.</tt><tt class="py-op">)</tt> </tt>
<a name="L46"></a><tt class="py-lineno">46</tt>  <tt class="py-line">                        <tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">logz</tt> <tt class="py-op">=</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">sum</tt><tt class="py-op">(</tt><tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">log</tt><tt class="py-op">(</tt><tt class="py-number">1.</tt> <tt class="py-op">+</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">exp</tt><tt class="py-op">(</tt><tt class="py-name">self</tt><tt class="py-op">.</tt><tt class="py-name">b</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
</div></div><a name="L47"></a><tt class="py-lineno">47</tt>  <tt class="py-line"> </tt><script type="text/javascript">
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